Monolingual versus Multilingual BERTology for Vietnamese Extractive Multi-Document Summarization
This work addresses a gap in applying BERT to Vietnamese text summarization, but it is incremental as it adapts existing methods to a new language.
The paper tackled extractive multi-document summarization for Vietnamese by comparing monolingual and multilingual BERT models, finding that monolingual models achieve promising results, though no specific performance numbers are provided.
Recent researches have demonstrated that BERT shows potential in a wide range of natural language processing tasks. It is adopted as an encoder for many state-of-the-art automatic summarizing systems, which achieve excellent performance. However, so far, there is not much work done for Vietnamese. In this paper, we showcase how BERT can be implemented for extractive text summarization in Vietnamese on multi-document. We introduce a novel comparison between different multilingual and monolingual BERT models. The experiment results indicate that monolingual models produce promising results compared to other multilingual models and previous text summarizing models for Vietnamese.